INTRODUCTION It is understood in the scientific community that being able to easily identify the data used in research allows scientists to either reproduce and verify the results reported, or build on the findings to produce new results. The _Mikulski Archives for Space Telescopes_ (MAST) team at the Space Telescope Science Institute (STScI) began an exploration of Digital Object Identifiers (DOIs) as a way to directly attach MAST data to scientific results in the literature. A digital object identifier provides an "actionable, interoperable, persistent link" [1] which relies on a structure which has been standardized and used globally since 2000. MAST staff identified the following issues they considered resolvable through the use of DOIs: - MAST data used in journal articles are referred to in an inconsistent fashion, making it at times difficult for later authors to reproduce or expand on the work. - Links to data provided in articles tend to decay (rot) over time. (see pepe et al) - It is difficult and time consuming for MAST/STScI staff to track precisely what data are being used for attribution and telescope bibliometrics. A proposal was put forward and implemented for a service with which authors can find or generate Digital Object Identifiers that are associated with the data they analyzed in their publication. Early in the process STScI staff recognized an alliance with an established journal would be critical to the success of the project. American Astronomical Society (AAS) Journals were an obvious partner, due to their large marketshare of MAST publications (~50%) and ongoing collaborations with MAST astronomers. MAST staff call this _The DOI Project_ internally and the _MARC_ project with our partners. [1] https://www.doi.org/factsheets/DOIKeyFacts.html

We have developed a method for deriving the distribution of the Milky Way’s interstellar medium as a function of longitude, latitude, distance and line-of-sight velocity. This method takes as input maps of reddening as a function of longitude, latitude, and distance and maps of line emission as a function of longitude, latitude, and line-of-sight velocity. We have applied this method to datasets covering much of the Galactic plane. The output of this method correctly reproduces the line-of-sight velocities of high-mass star forming regions with known distances from and qualitatively agrees with results from the Milky Way kinematics literature. These maps will be useful for measuring flows of gas around the Milky Way’s spiral arms and into and out of giant molecular clouds.

We present medium-resolution, near-ultraviolet VLT/FLAMES observations of the star USNO-A0600-15865535. We adapt a standard method of stellar typing to our measurement of the shape of the Balmer ϵ absorption line to demonstrate that USNO-A0600-15865535 is a blue horizontal branch star, residing in the lower stellar halo at a distance of 4.4 kpc from the Sun. We measure the H & K lines of singly-ionized calcium and find two isolated velocity components, one originating in the disk, and one associated with high-velocity cloud complex WD. This detection demonstrated that complex WD is closer than 4.4 kpc and is the first distance constraint on the +100 km/s Galactic complex of clouds. We find that Complex WD is not in corotation with the Galactic disk as has been assumed for decades. We examine a number of scenarios, and find that the most likely is that Complex WD was ejected from the solar neighborhood and is only a few kpc from the Sun.

The community of astronomical strawmen says that $\RV$ should correlate with ISM density – dust grows and/or agglomerates in dense structures. We can look for this correlation in the intersection of the Valencic+ (year) and Jenkins (2009) samples. Valencic+ provides extinction information, including $\RV$, and Jenkins provides ISM density and dust-to-gas ratio information along the same lines of sight. However, while there is a clear correlation between density and the dust-to-gas ratio (Figure [fig:nH_F]), there does not appear to be a correlation between density and $\RV$ (Figure [fig:lognH_RV]). By looking at Eddie’s map of $\RV$ over a large area, we can generate the hypothesis that there’s not a clear density-$\RV$ correlation because much of the $\RV$ variation in Eddie’s map happens on much larger spatial scales than the angular size of a dense ISM structure. There could be a density-$\RV$ relationship on top of this large-scale variation, but there isn’t a clear $\EBV$ vs. $\RV$ correlation because the large-scale variation has a higher magnitude. So, if we want to look for an $\EBV$ vs. $\RV$ correlation, we need to filter out the large scale structure. One way to do this is to look at differences in $\EBV$ vs. differences in $\RV$ between pairs of sightlines as a function of the sightlines’ separations.

INTRODUCTION Filaments are ubiquitous in the interstellar medium. They have been identified in molecular gas for some time , and with higher resolution and sensitivity surveys they are being found throughout the Galactic interstellar medium (ISM) . More recently the filaments have been identified in the Galactic ISM in atomic form . The properties of the HI filaments and their relationship to the molecular filaments largely remains to be determined. Filaments appear to precede star formation in the cold ISM and are thought to be linked to a process active in the gas cloud . The low density atomic filaments may represent the starting point of the filament formation process, i.e., the convergence of the gas that forms the molecular filaments. On the other hand, the structures may be created naturally in the ISM with no direct connection to the gravitationally dominated molecular filaments. The primary feature of the HI filaments that has been highlighted so far is their alignment with the Galactic magnetic field . This infers the filaments are linked to an aligned ionized gaseous component. characterized the filamentary structure he found in the all-sky HI survey with 11 − 16resolution, though it was all of the structures found after completing an unsharp mask on the data and therefore does not isolate individual filaments. identified the orientation of the linear HI features in the GALFA-HI data used here (4and 0.18 resolution) using a rolling hough transform (RHT). The RHT rolls across the image with a circular window and identifies structures that follow the diameter of the circle at the range of possible angles. This method gives alignment information, but does not extract the individual fibers in the cube to define them further as physical structures. It also requires setting a preferred velocity binning before applying the RHT. The focussed on denser structures in a cloud detected in HI absorption towards the Galactic Center. Though distinct from the diffuse HI filaments being examined in emission here, they serve as another useful comparison point. For the molecular filaments, numerous properties have been extracted and studied (REFS). One property in particular that has garnered much attention is the width of the filaments. This width could determine..... Though there was some initial excitement on the filaments having a uniform width of approximately 0.1 pc , this has since been found to ADD PANAU PAPER INFO The velocity structure of the atomic filaments indicates if the filaments are actively flowing across their length, or potentially rotating along the short axis. If no velocity gradient is evident, the dispersion is representative of the level of turbulence in the gas and the temperature of the gas. The width http://arxiv.org/abs/1608.02601 find similar results to C14 that the filaments are aligned with the Galactic magnetic field using a three dimensional shock compression model to represent the Local Bubble. They find that the likely formation of the HI fibers is the turbulent shear strain consistent with . Quoted from Panapoulo paper for reference In studies of sub/trans-Alfv´enic turbulence, where the magnetic field is dynamically important, filament orientations with respect to the large scale ordered field, depend on whether gravity is important. In simulations where gravity is not taken into account (e.g. Falceta-Gon¸calves et al. 2008) or structures are gravitationally unbound (Soler et al. 2013), filaments are parallel to the magnetic field. filaments in wind blown bubble sim ref http://adsabs.harvard.edu/abs/2011ApJ...731...13N Properties papers Striations in the Taurus molecular cloud: Kelvin-Helmholtz instability or MHD waves? http://arxiv.org/abs/1606.08858 arXiv:1607.00005 Date: Thu, 30 Jun 2016 20:00:05 GMT (4386kb) Title: The magnetic field and dust filaments in the Polaris Flare Authors: G. V. Panopoulou, I. Psaradaki, K. Tassis Categories: astro-ph.GA astro-ph.SR Comments: 14 pages, 12 figures, accepted by MNRAS In diffuse molecular clouds, possible precursors of star-forming clouds, the effect of the magnetic field is unclear. In this work we compare the orientations of filamentary structures in the Polaris Flare, as seen through dust emission by Herschel, to the plane-of-the-sky magnetic field orientation ($\rm B_{pos}$) as revealed by stellar optical polarimetry with RoboPol. Dust structures in this translucent cloud show a strong preference for alignment with $\rm B_{pos}$. 70 filaments (within 30∘). We explore the spatial variation of the relative orientations and find it to be uncorrelated with the dust emission intensity and correlated to the dispersion of polarization angles. Concentrating in the area around the highest column density filament, and in the region with the most uniform field, we infer the $\rm B_{pos}$ strength to be 24 − 120 μG. Assuming that the magnetic field can be decomposed into a turbulent and an ordered component, we find a turbulent-to-ordered ratio of 0.2 − 0.8, implying that the magnetic field is dynamically important, at least in these two areas. We discuss implications on the 3D field properties, as well as on the distance estimate of the cloud. ( https://arxiv.org/abs/1607.00005 , 4386kb) Title: Neutral hydrogen and magnetic fields in M83 observed with the SKA Pathfinder KAT-7 Authors: G. Heald, W.J.G. de Blok, D. Lucero, C. Carignan, T. Jarrett, E. Elson, N. Oozeer, T.H. Randriamampandry, L. van Zee We show that the magnetic field of M83 is similar in form to other nearby star forming galaxies, and suggest that the disk-halo interface may host a large-scale regular magnetic field. ( https://arxiv.org/abs/1607.03365 OBSERVATIONAL DATA AND ANALYSIS METHODS The observational data are from the Galactic Arecibo L-band Feed Array HI survey 2nd data release (GALFA-HI DR2; Peek et al. 2016). The survey covers HI velocities from -650 to +650 with a 0.184 channel spacing, 4$\arcmin$ spatial resolution, and a sensitivity of 150 mK per 1 bin (equivalent to a 5σ column density sensitivity of ∼1.4 × 10¹⁸ cm−2). Here we focus on HI fibers in regions with absolute Galactic Latitude greater than 30 degrees to minimize the background Galactic HI that needed to be removed and examined the velocity range +50 to -50 (see example channel in Figure ). The fibers were identified in the GALFA data with FilFinder ; however since this program was written to find filaments in two-dimensional data, we made substantial additions to recover the velocity dimension of the fibers. FilFinder identifies filaments in images with the following pre-processing steps: 1. Flattens the image with an arctan transform to remove the effect of small bright features, 2. Smooths the image with a median filter to limit the fragmentation of filaments WHAT DID WE USE FOR SMOOTHING RADIUS? 3. Applies an adaptive threshold in that the intensity of the central pixel must be greater than median of the neighborhood around it. PATCH SIZE WE USED? 4. Remove small spurious objects with a cut on the total area of objects and applying a small median filter. We chose a total area of 600 square pixels as the size threshold. The preprocessing steps prepare a mask that can be used to identify the filaments. Structures are identified within the mask with a medial axis transform that puts objects into 1-pixel wide skeletons maximized in one direction. The final step of FilFinder is to prune the skeletons to be filaments. This involves adopting the long axis as the body of the filament and removing small offshoots in other directions. See the paper for more details on the 2D filament identification process. To identify the velocity structure of the fibers we run FilFinder on each individual channel images and then determine the spatial overlap between fibers in adjacent channels. Specifically, the steps for identifying 3D fibers in the GALFA data with FilFinder are as follows: - An unsharped mask with a smoothing radius of 30$\arcmin$ was applied to each channel to remove the diffuse Galactic emission. A data cube with a smoothing radius of 15$\arcmin$ was also examined for comparison and the properties of several fibers were checked outside of the FilFinder with a 45$\arcmin$ unsharped mask. - FilFinder is run on the each channel of the GALFA-HI cube and the objects found are identified with a bottom left and top right corner set, and a velocity slice index. - The area encompassing objects in adjacent channels are compared and if there is a >75% overlap between the areas of objects in the two channels they are merged as part of the same structure. The object is discontinued when there is no longer a 75% overlap in an adjacent channel. - The final catalog of three dimensional objects was trimmed to exclude those filaments with sizes <5000 pixels and aspect ratios >2. This cut was necessary to reduce the large number of objects found and optimizes the filaments to be long, thin structures. This is different from how the HI fibers were identified in with the Rolling Hough Transform (RHT). With the RHT filaments were identified blah..... To extract the fiber properties from the cube we create three distinct maps: 1. an integrated intensity (moment 0) map to obtain column densities, lengths and masses, 2. an average velocity (moment 1) map to examine velocity gradients along the filaments, and 3. a velocity dispersion (moment 2) map to examine the velocity widths. These maps are created using the _moment_ task within Miriad on the USM cubes. The actual values are obtained from these moment maps by isolating the fiber in position and extracting the typical values for the fibers. Though somewhat labor intensive, the combination of using the USM cube and isolating in position was found to be the best way to isolate the fiber from the abundant additional surrounding diffuse Galactic emission. Signatures of velocity gradients were largely examined by eye (see Figure ). The typical width of the fibers is an important property to derive from the observations given how it factors in to other physical properties and the predictions from simulations. The width was not easy to obtain from the integrated intensity maps as there are variations in this parameter along the lengths of the fibers. We utilized the FiLTer program of on the RHT fibers to obtain the typical widths of the HI fibers. This therefore extracts the width properties of all of the RHT identified fibers in Figure . FiLTer...ADD BRIEF FILTER DESCR SHOULD PROBABLY COMPARE THIS TO WHAT YOU WOULD EXTRACT BY EYE FOR MIN/MAX. IF PROGRAM ISN’T BEHAVING GO BACK TO THIS IDEA WITH UG RESULTS The properties of the filaments are shown in Table [props.tab]. The physical properties of width, length, volume density, pressure and HI mass are derived assuming the filaments are at a distance of 100 pc. An estimate for the temperature is obtained from the linewidth of the fiber, which is derived from the average dispersion for the cloud, T (K) = 21.8 (2.355\sigma)^2 This is an upper limit on the temperature as any turbulent component to the dispersion is not removed. The thermal pressure can be estimated using, P_{\rm th}/k (K cm^{-3})= n_H T but this is an upper limit on the thermal pressure given the temperature is an upper limit. Given our data, a derivation of the total pressure from the dispersion is more relevant. P = \sigma^2 1.4 m_H n_H THESE TWO ARE DIRECTLY RELATED SINCE VARIABLES IN BOTH ARE THE SAME, SO PROBABLY ONLY INCLUDE ONE. DISCUSSION Following , we can constrain the strength of the magnetic field by assuming the alignment of the fibers with the field indicates it is the mechanism dominating its observed structure. The magnetic energy density should therefore be larger than the kinetic and gravitational energy densities. relevant section from Papadoulo paper on relevant other papers In a series of papers the Planck collaboration compared the magnetic field to ISM structure across a range of hydrogen column densities (NH). Planck Collaboration Int. XXXII (2014) considered the orientation of structures in the diffuse ISM in the range of NH ∼ 1020 − 1022 and found significant alignment with the plane-of-the-sky magnetic field (Bpos). Planck Collaboration Int. XXXV (2015) found that in their sample of 10 nearby clouds, substructure at high column density tends to be perpendicular to the magnetic field, whereas at low column density there is a tendency for alignment. Studies of optical and NIR polarization, tracing Bpos in cloud envelopes, show that dense filaments within star-forming molecular clouds tend to be perpendicular to the magnetic field (Pereyra & Magalh˜aes 2004; Alves et al. 2008; Chapman et al. 2011; Sugitani et al. 2011). On the other hand, there are diffuse linear structures termed striations, that share a common smoothly varying orientation and are situated either in the outskirts of clouds (Goldsmith et al. 2008; Alves de Oliveira et al. 2014) or near dense filaments (Palmeirim et al. 2013). These structures show alignment with Bpos (van den Bergh 1956; Chapman et al. 2011; Palmeirim et al. 2013; Alves de Oliveira et al. 2014; Malinen et al. 2015). The extremely well-sampled data of Franco & Alves (2015) in Lupus I show that Bpos is perpendicular to the cloud’s main axis but parallel to neighbouring diffuse gas. There are, however, exceptions to this trend (e.g. L1506 in Taurus, Goodman et al. 1990).

INTRODUCTION We are interested in GALFA-HI fibers. They tell us about the B-field. But how do they relate the microphysics? Two important unanswered questions are: do they have a characteristic width? There are arguments for a particular width, but GALFA-HI does not have the resolution to resolve them. And what is their dust content? Small grains control ISM heating, as they dominate the surface area, large grains control ISM metal content, as they dominate the grain volume. Both are important indicators of the content of the fibers. To check these we use Planck 353 emission data and WISE emission maps from and compare to the GALFA-HI DR2 data cubes

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INTRODUCTION ACS/WFC images can suffer from a number of optical and scattered light anomalies. Most of the optical anomalies that effect ACS have been well characterized. Hardware, software, and optical anomalies are discussed in ISR 2008-01. This is not the case for the scattered light anomalies known as “dragon’s breath” and edge glow. Dragon’s breath is caused by reflections being scattered back to the detector. There is a knife-edged mask in front of the CCD that scatters light back to the detector when its back side is illuminated by reflections from the CCD surface. These phenomena were discovered in early testing of ACS and were mitigated by sharpening the knife edges and coating them black. However, when point sources fall on the edge of the mask, scattering still occurs (Hartig et. al.).

The WorldWide Telescope (WWT) software environment gives explorers a Universe at their fingertips. Views of the Sky at wavelengths invisible to the human eye, virtual "3D" space travel, and seamless connections to the ever-expanding web of information online about our understanding of the Universe are available to anyone seeking to explore. WWT lets teachers and students learn in completely new, more engaging and data-rich ways, and it lets scientists communicate results, and share and contextualize data much more effectively than they ever have before. In this short article, written to commemorate the full "open-sourcing" of WorldWide Telescope software by Microsoft in 2015, we highlight just a few of the ways WWT has, and will continue to, change education, research, and scholarly communication. Detailed examples of how WorldWide Telescope is used in various settings are described at wwtstories.org.

We aim to observe 7 targets in M33 with COS. Unfortunately, M33 has a large amount of diffuse structure, especially at the 5'' beam of GALEX, and so it is difficult to use the standard GALEX AIS to clear these targets. We wish to use the existing data, consisting of FUSE spectra of each target, and deep NGS GALEX imaging to a) clear the targets from dangerously bright objects and b) get the best guess as to the flux from these targets to use for flux estimation for buffer timing and SNR estimation. Additionally, precise targeting in giant HII regions such as NGC 604 is difficult, as compact sources are hard to discern.

_A 5-minute video demonstration of this paper is available at this YouTube link._ PREAMBLE A variety of research on human cognition demonstrates that humans learn and communicate best when more than one processing system (e.g. visual, auditory, touch) is used. And, related research also shows that, no matter how technical the material, most humans also retain and process information best when they can put a narrative "story" to it. So, when considering the future of scholarly communication, we should be careful not to do blithely away with the linear narrative format that articles and books have followed for centuries: instead, we should enrich it. Much more than text is used to communicate in Science. Figures, which include images, diagrams, graphs, charts, and more, have enriched scholarly articles since the time of Galileo, and ever-growing volumes of data underpin most scientific papers. When scientists communicate face-to-face, as in talks or small discussions, these figures are often the focus of the conversation. In the best discussions, scientists have the ability to manipulate the figures, and to access underlying data, in real-time, so as to test out various what-if scenarios, and to explain findings more clearly. THIS SHORT ARTICLE EXPLAINS—AND SHOWS WITH DEMONSTRATIONS—HOW SCHOLARLY "PAPERS" CAN MORPH INTO LONG-LASTING RICH RECORDS OF SCIENTIFIC DISCOURSE, enriched with deep data and code linkages, interactive figures, audio, video, and commenting.

INTRODUCTION The preparations for the launch of JWST offer an opportunity for STScI to take advantage of emerging technologies to create a written communication output on-par with its scientific output. The Free Open Source Software (FOSS) community has had similiar requirements as STScI to create extensive technical documentation. These FOSS projects, including the partially STScI-funded Astropy software package, including dozens of geographically seperated authors with a rapid document release cycle. This document outlines the underlying technologies used by Astropy and other software projects and explores various implementations that STScI could use to produce user information of similar quality. The modern web is full of powerful tools that were once restricted to local processes. Advances in web technology have made online collaboration the norm from Google Docs to Facebook. These are often distinct from their predecessors in that they and truly web-based, not just web-enhanced; everything happens in the browser. This software model, called Software as a Service (SaaS) as opposed to the more traditional Software as a Product (SaaP) offers a lightweight and rapidly evolving ecosystem.

Both the global research community and federal governments are embracing a move toward more open sharing of the products of research. Historically, the primary product of research has been the peer-reviewed journal article for fundamental research and government technical report for applied research and engineering for government sponsored research. However, advances in information technology, new “open access” business models, and government policies are working to make publications and supporting materials much more accessible to the general public. These same drivers are obscuring the distinction between the data generated through the course of research and the associated publications. These developments have the potential to significantly enhance the value of both publications and the supporting digital research data, turning them into valuable assets that can be shared and reused by other researchers. The confluence of these shifts in the research landscape leads one to the conclusion that technical publications and their supporting research data must become bound together in a rational fashion. However, bringing these two research products together will require establishment of new policies and a supporting data infrastructure that have essentially no precedent in the materials community, and indeed are stressing many other fields of research. This document raises the key issues that must be addressed in developing these policies and infrastructure, and suggests a path forward in creating the solutions.

In the last portion of _Sidereus Nuncius_, Galileo reported his discovery of FOUR OBJECTS that appeared to form a straight line of stars near JUPITER. The first night, he witnessed a line of three little stars close to Jupiter parallel to the ecliptic; the following nights brought different arrangements and another star into his view, totaling four stars around Jupiter. Throughout the text, Galileo gave illustrations of the relative positions of Jupiter and its apparent companion stars as they appeared nightly from late January through early March 1610. The fact that they changed their positions relative to Jupiter from night to night, but always appeared in the same straight line near Jupiter, brought Galileo to deduce that they were four bodies in orbit around Jupiter. On January 11 after 4 nights of observation he wrote: “I therefore concluded and decided unhesitatingly, that there are three stars in the heavens moving about Jupiter, as Venus and Mercury round the Sun; which at length was established as clear as daylight by numerous subsequent observations. These observations also established that there are not only three, but four, erratic sidereal bodies performing their revolutions round Jupiter...the revolutions are so swift that an observer may generally get differences of position every hour.”

A central problem in convex algebra is the extension of left-smooth functions. Let $$ be a combinatorially right-multiplicative, ordered, standard function. We show that ℓI, Λ ∋ 𝒴U, 𝔳 and that there exists a Taylor and positive definite sub-algebraically projective triangle. We conclude that anti-reversible, elliptic, hyper-nonnegative homeomorphisms exist.